Skip multi-second Python LLM graph-building jobs (cognee.cognify) and get synchronous <15 ms writes, 12.9 ms recall, and 30 MCP tools out of the box.
| Criterion | Memoria | Cognee |
|---|---|---|
| LongMemEval Accuracy (500 q) | 100.0% (500 / 500) | Not published on full 500-q LongMemEval |
| Multilingual / Hebrew LongMemEval | 100.0% (102 / 102 · 98%+ enterprise bar · 15 languages) | LLM prompt dependent |
| Recall & Code Query Latency | <20ms (12.9 ms avg) | 250–1,400 ms + batch cognify() pipeline |
| LLM Token Cost per Write | 0 tokens ($0) | Multi-step LLM ECL extraction pipeline |
| Belief Revision on State Change | Automatic Supersedes revision | Graph re-indexing pass |
| IDE & MCP Ecosystem | 15 AI clients auto-configured · 30 MCP tools | 14 MCP tools (Python server) |
| 1-Click Migration Importer | CLAUDE.md, .cursorrules, Mem0 JSON, ChatGPT & Claude | Custom script required |
| Pricing | $0 Free (1,000 calls) · $19 / $79 / $299 mo | Open-source + usage cloud tiers |
Choose Cognee if your workflow is centered on offline batch document ingestion pipelines in Python.
Choose Memoria for real-time interactive coding and production agents where every turn, user correction, and git commit must be indexed deterministically in <15 ms with zero LLM cost.
1. Create your free Memoria account (1,000 API calls & memories included).
2. Open Memory Explorer on /account and paste your Cognee JSON export, CLAUDE.md, or .cursorrules.
3. Run the one-line installer below to connect all 15 AI coding clients:
curl -fsSL https://memoria.kolivri.com/downloads/install.sh | MEMORIA_KEY=mem_dev_your_key_here bash